Teradata Package for R Function Reference | 17.20 - Unpack - Teradata Package for R - Look here for syntax, methods and examples for the functions included in the Teradata Package for R.

Teradata® Package for R Function Reference

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for R
Release Number
17.20
Published
March 2024
ft:locale
en-US
ft:lastEdition
2024-05-03
dita:id
TeradataR_FxRef_Enterprise_1720
lifecycle
latest
Product Category
Teradata Vantage

Unpack

Description

The Unpack function unpacks data from a single packed column into multiple columns. The packed column is composed of multiple virtual columns, which become the output columns. To determine the virtual columns, the function must have either the delimiter that separates them in the packed column or their lengths.
Note: This function is only available when tdplyr is connected to Vantage 1.1 or later versions.

Usage

  td_unpack_sqle (
      data = NULL,
      input.column = NULL,
      output.columns = NULL,
      output.datatypes = NULL,
      delimiter = ",",
      column.length = NULL,
      regex = "(.*)",
      regex.set = 1,
      exception = FALSE,
      data.order.column = NULL
  )

Arguments

data

Required Argument.
Specifies the tbl_teradata containing the input attributes.

data.order.column

Optional Argument.
Specifies Order By columns for "data".
Values to this argument can be provided as a vector, if multiple columns are used for ordering.
Types: character OR vector of Strings (character)

input.column

Required Argument.
Specifies the name of the input column that contains the packed data.
Types: character

output.columns

Required Argument.
Specifies the names to give to the output columns, in the order in which the corresponding virtual columns appear in "input.column".If you specify fewer output column names than there are virtual input columns, the function ignores the extra virtual input columns. That is, if the packed data contains x+y virtual columns and the "output.columns" argument specifies x output column names, the function assigns the names to the first x virtual columns and ignores the remaining y virtual columns.
Types:character OR vector of Strings (characters)

output.datatypes

Required Argument.
Specifies the datatypes of the unpacked output columns. Supported values for this argument are VARCHAR, integer, numeric, TIME, DATE, and TIMESTAMP. If "output.datatypes" specifies only one value and "output.columns" specifies multiple columns, then the specified value applies to every "output.column". If "output.datatypes" specifies multiple values, then it must specify a value for each "output.column". The nth datatype corresponds to the nth "output.column".The function can output only 16 VARCHAR columns.
Types:character OR vector of Strings (characters)

delimiter

Optional Argument.
Specifies the delimiter (a string) that separates the virtual columns in the packed data. The default delimiter is comma (,). If the virtual columns are separated by a delimiter, then specify the delimiter with this argument; otherwise, specify the "column.length" argument. Do not specify both this argument and the "column.length" argument.
Default Value: ","
Types: character

column.length

Optional Argument.
Specifies the lengths of the virtual columns; therefore, to use this argument, you must know the length of each virtual column. If "column.length" specifies only one value and "output.columns" specifies multiple columns, then the specified value applies to every output column. If "column.length" specifies multiple values, then it must specify a value for each output column. The nth datatype corresponds to the nth output column. However, the last "column.name" can be an asterisk (*), which represents a single virtual column that contains the remaining data. For example, if the first three virtual columns have the lengths 2, 1, and 3, and all remaining data belongs to the fourth virtual column, you can specify column.length ("2", "1", "3", *). If you specify this argument, you must omit the delimiter argument.
Types:character OR vector of Strings (characters)

regex

Optional Argument.
Specifies a regular expression that describes a row of packed data, enabling the function to find the data values. A row of packed data contains one data value for each virtual column, but the row might also contain other information (such as the virtual column name). In this argument "regex", each data value is enclosed in parentheses. For example, suppose that the packed data has two virtual columns, age and sex, and that one row of packed data is: age:34,sex:male, the "regex" that describes the row is ".*:(.*)". The ".*:" matches the virtual column names, age and sex, and the "(.*)" matches the values, 34 and male. The default "regex" is "(.*)" which matches the whole string (between delimiters, if any). When applied to the preceding sample row, the default "regex" causes the function to return "age:34" and "sex:male" as data values. To represent multiple data groups in "regex", use multiple pairs of parentheses. By default, the last data group in "regex" represents the data value (other data groups are assumed to be virtual column names or unwanted data). If a different data group represents the data value, specify its group number with the "regex.set" argument.
Default Value: "(.*)"
Types: character

regex.set

Optional Argument.
Specifies the ordinal number of the data group in "regex" that represents the data value in a virtual column. By default, the last data group in "regex" represents the data value. For example, suppose that "regex" is: "([a-zA-Z]*):(.*)" If group_number is "1", then "([a-zA-Z]*)" represents the data value. If group_number is "2", then "(.*)" represents the data value.
Default Value: 1
Types: integer

exception

Optional Argument.
Specifies whether the function ignores rows that contain invalid data; that is, it continues without outputting them, which causes the function to fail if it encounters a row with invalid data.
Default Value: FALSE
Types: logical

Value

Function returns an object of class "td_unpack_sqle" which is a named list containing object of class "tbl_teradata".
Named list member can be referenced directly with the "$" operator using the name: result.

Examples

  
    # Get the current context/connection.
    con <- td_get_context()$connection
    
    # Load example data.
    loadExampleData("unpack_example", "ville_tempdata", "ville_tempdata1")
    
    # Create object(s) of class "tbl_teradata".
    ville_tempdata <- tbl(con, "ville_tempdata")
    ville_tempdata1 <- tbl(con, "ville_tempdata1")
    
    # Example 1 - Using the delimiter argument.
    td_unpack_out1 <- td_unpack_sqle(data = ville_tempdata,
                        input.column = "packed_temp_data",
                        output.columns = c("city","state","temp_F"),
                        output.datatypes = c("varchar","varchar","real"),
                        delimiter = ",",
                        regex = '(.*)',
                        regex.set = 1,
                        exception = TRUE
                        )
    
    # Example 2 - Using column.length argument
    td_unpack_out2 <- td_unpack_sqle(data = ville_tempdata1,
                        input.column = "packed_temp_data",
                        output.columns = c("city","state","temp_F"),
                        output.datatypes = c("varchar","varchar","real"),
                        column.length = c("9","9","4"),
                        regex = '(.*)',
                        regex.set = 1,
                        exception = TRUE
                        )